Rui Pereira

Rui Abreu, Marco Couto, Luís Cruz et al.

This report describes the research goals and results of the Green Software Lab (GSL) research project. This was a project funded by Fundação para a Ciência e a Tecnologia (FCT) -- the Portuguese research foundation -- under reference POCI-01-0145-FEDER-016718, that ran from January 2016 till July 2020. This report includes the complete document reporting the results achieved during the project execution, which was submitted to FCT for evaluation on July 2020. It describes the goals of the project, and the different research tasks presenting the deliverables of each of them. It also presents the management and result dissemination work performed during the project's execution. The document includes also a self assessment of the achieved results, and a complete list of scientific publications describing the contributions of the project. Finally, this document includes the FCT evaluation report.

Rui Pereira, Marco Couto, Jácome Cunha et al.

This paper presents a detailed study of the energy consumption of the different Java Collection Framework (JFC) implementations. For each method of an implementation in this framework, we present its energy consumption when handling different amounts of data. Knowing the greenest methods for each implementation, we present an energy optimization approach for Java programs: based on calls to JFC methods in the source code of a program, we select the greenest implementation. Finally, we present preliminary results of optimizing a set of Java programs where we obtained 6.2% energy savings.

Jácome Cunha, João Paulo Fernandes, Rui Pereira et al.

One of the most important assets of any company is being able to easily access information on itself and on its business. In this line, it has been observed that this important information is often stored in one of the millions of spreadsheets created every year, due to simplicity in using and manipulating such an artifact. Unfortunately, in many cases it is quite difficult to retrieve the intended information from a spreadsheet: information is often stored in a huge unstructured matrix, with no care for readability or comprehensiveness. In an attempt to aid users in the task of extracting information from a spreadsheet, researchers have been working on models, languages and tools to query. In this paper we present an empirical study evaluating such proposals assessing their usage to query spreadsheets. We investigate the use of the Google Query Function, textual model-driven querying, and visual model-driven querying. To compare these different querying approaches we present an empirical study whose results show that the end-users' productivity increases when using model-driven queries, specially using its visual representation.